Guidelines on Face Attributes

Amazon Rekognition returns a bounding box, attributes, emotions, landmarks, quality,
and the pose for each face it detects.
Each attribute or emotion has a value and a confidence score. For example, a certain
face might be found as ‘Male’ with a
confidence score of 90% or having a ‘Smile’ with a confidence score of 85%. We recommend
using a threshold of 99% or more
for use cases where the accuracy of classification could have any negative impact
on the subjects of the images. The only
exception is Age Range, where Amazon Rekognition estimates the lower and upper age
for the person. In this case, the wider the
age range, the lower the confidence for that prediction. As an approximation, you
should use the mid-point of the age
range to estimate a single value for the age of the detected face. (The actual age
does not necessarily correspond to this number.)

One of the best uses of these attributes is generating aggregate statistics. For example,
attributes, such as Smile, Pose, and
Sharpness, may be used to select the ‘best profile picture’ automatically in a social
media application. Another common use case
is estimating demographics anonymously of a broad sample using the gender and age
attributes (for example, at events or retail stores).

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